SCENT

GIT PAPER

Authors: S. Sakaue

SCENT uses single-cell multimodal data (e.g., 10X Multiome RNA/ATAC) and links ATAC-seq peaks (putative enhancers) to their target genes by modeling association between chromatin accessibility and gene expression across individual single cells.

HLA imputation and association tutorial

GIT PAPER

Authors: S. Sakaue

A thorough tutorial on HLA imputation and association, accompanying our manuscript “Tutorial: A statistical genetics guide to identifying HLA alleles driving complex disease”.
The tutorial consists of two parts:

• HLA imputation : We introduce protocols to QC genotype, perform haplotype phasing and HLA imputation. We provide useful scripts and example usage, with example genotype and reference datasets.
• HLA association and fine-mapping: We introduce various statistical methods to identify and fine-map disease-associated HLA variations. The HLA imputation results from section #1 will be used. We provide useful scripts with some example phenotype data.

KIR Analysis Platform

GIT PAPER

Authors: S. Sakaue

A genomic pipeline to genotype KIR types and copy numbers from sequencing data.

GREP: Genome for REPositioning drugs

GIT

Authors: S. Sakaue

GREP can quantify an enrichment of the user-defined set of genes in the target of clinical indication categories and capture potentially repositionable drugs targeting the gene set.

PheWeb.jp

WEBSITE PAPER

This website releases genome-wide association study (GWAS) summary statistics of our paper conducting meta-analyses of BioBank Japan, UK Biobank and FinnGen for >200 medical phenotypes.